A new model based on the Bayesian approach has been developed which has interesting connections with the vector models of G. Salton. Theoretical details have been worked out. Ideally documents must be indexed by the "real" objects that they refer to and these real objects become nodes in a system of multiple hierarchies called a specificity network. Each hierarchy is produced by a specificity operator and results in a tree of objects starting at the root with the most general and moving to greater specificity as one progresses towards the leaves. The objects which populate nodes are represented by textual terms or phrases. There may be many representations of any single object. The model described is labor intensive to construct if each document must be converted by hand to a form suitable to represent the objects discussed within it. Thus we are developing methods of automatic extraction of object representations. This will lead to a tractable task to represent documents. Our major effort is to develop machine learning methods that can aid in the construction of the hierarchies described here.